TY - GEN
T1 - VisCollage
T2 - 17th IEEE Pacific Visualization Conference, PacificVis 2024
AU - Li, Xiao Han
AU - Hung, Yi Ting
AU - Pan, Jia Yu
AU - Lin, Wen Chieh
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - While existing visualization systems excel in exploring datasets and discovering data patterns and insights, challenges remain in automatically generating infographics from exploration-derived visualizations. We propose VisCollage, a computational pipeline that automatically organizes and renders charts from an exploration in a 'visual collage', which is inspired by data journalism and can be viewed as a kind of 'partitioned poster infographic'. By analyzing the relation (e.g., drill-down or comparison) between charts established during exploration, VisCollage groups and merges them to reduce data redundancy. In addition, VisCollage automatically identifies a main chart of the exploration and arranges annotations and background charts around it. User studies evaluated from the perspectives of creators, professional data journalists, and general readers indicate that our system assists creators in generating satisfactory visualization summaries of data events, enables the general audience to extract insights from the data through visual collages, and are well received by professionals.
AB - While existing visualization systems excel in exploring datasets and discovering data patterns and insights, challenges remain in automatically generating infographics from exploration-derived visualizations. We propose VisCollage, a computational pipeline that automatically organizes and renders charts from an exploration in a 'visual collage', which is inspired by data journalism and can be viewed as a kind of 'partitioned poster infographic'. By analyzing the relation (e.g., drill-down or comparison) between charts established during exploration, VisCollage groups and merges them to reduce data redundancy. In addition, VisCollage automatically identifies a main chart of the exploration and arranges annotations and background charts around it. User studies evaluated from the perspectives of creators, professional data journalists, and general readers indicate that our system assists creators in generating satisfactory visualization summaries of data events, enables the general audience to extract insights from the data through visual collages, and are well received by professionals.
KW - Data Presentation
KW - Infographics
KW - Narrative Visualization
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=85195913788&partnerID=8YFLogxK
U2 - 10.1109/PacificVis60374.2024.00036
DO - 10.1109/PacificVis60374.2024.00036
M3 - Conference contribution
AN - SCOPUS:85195913788
T3 - IEEE Pacific Visualization Symposium
SP - 262
EP - 271
BT - Proceedings - 2024 IEEE 17th Pacific Visualization Conference, PacificVis 2024
PB - IEEE Computer Society
Y2 - 23 April 2024 through 26 April 2024
ER -